In a system for the Simulation of Area Weapons Effects (SAWE), conventional land-mine effects are simulated by a Mine Effects Simulator (MES) to provide sensory cues for force-on-force, free-play combined arms field training exercises and other purposes. When a MES is detonated by a player, finely-divided inert powder is expelled with an audible bang as a smoke cue while a commercial flash bulb or flash powder is triggered to generate a flash cue that illuminates the smoke cue.
Single-shot, throw-away MES devices are planted on the terrain to simulate land mines. Just prior to detonation, an acoustic warning whistle is generated by the MES in the range of 2.8 kHz to 4.2 kHz for a period of about two seconds as a safety warning to personnel. Two frequencies are generated in each MES, and both decrease in frequency with time during the two seconds. Antipersonnel MES use tones A and B separated in frequency by 400 Hz, whereas antitank MES use tones A and C separated in frequency by 800 Hz. An acoustic warning whistle just prior to detonation will thus include tone A and tone B or C. While both tones A and B or C are to be detected, it is the difference in frequency for the second tone B or C as compared to tone A that is relied upon to determine whether it is an antipersonnel or an antitank mine that is being detonated. Thus, by setting the second tone of the warning whistle emitted by antipersonnel and antitank MES devices at different frequencies within the limited range and using Player Detector Devices (PDD's), real-time casualty assessment is possible after each MES detonation during training exercises. The two-second duration of the warning whistle allows the PDD to assess the acoustic tone received from a MES device through a microphone on the PDD. Consequently, assessment of the tones has a profound effect upon reliability of the real-time casualty assessment during field training exercises.
The longer the duration of the analysis, the greater the reliability of the PDD in rejecting false sounds, but the more it becomes possible to fail to record a "kill" of a fast moving vehicle that has set off a MES device because one to two seconds after running over a MES it could be outside the 10-meter casualty radius at the time of the audible bang, smoke expulsion and light flash. The selected timing of the SAWE-MES from the moment (T=0) the MES device is triggered is as follows:
T.sub.W =0.8 sec time to initiation of whistle at near full volume, PA1 T.sub.B =2.9 sec to initiation of a bang, and PA1 T.sub.F =3.4 sec to initiation of a flash.
The total time of the whistle warning at full volume before the bang is thus about 2 seconds with only another period of 0.5 sec before the flash. As a consequence, the Player Detector Device (PDD) has only about two seconds to detect the two-tone whistle and identify it as an antipersonnel mine simulator or an antitank mine simulator in order to accurately record a kill. This identification is important because an antipersonnel mine simulated by a MES device should not be recorded by a PDD carried on a tank. Thus, the problem addressed by the present invention is the prompt detection of two acoustic signals in a limited range (e.g., from 2.8 kHz to 4.2 kHz) in the presence of other acoustic signals and noise in general, and the proper identification of which tone signals have been received and periodically determining the difference in frequency between the two tones for the two-second duration of the whistle.
In the past, the PDD has been implemented with a Digital Signal Processor (DSP), a class of special purpose digital computers programmed for signal spectral analysis using a conventional Fast Fourier Transform (FFT) which, for real-time spectral analysis, depended upon high speed multiplication to detect the presence of the acoustic signals of predetermined tones. That implementation was too complex and required too much power for field use in PDDs of a SAWE-MES system. What is required is a less expensive PDD that requires less physical size, weight and operating power.
U.S. Pat. No. 4,031,462 is typical of prior-art real-time frequency analysis of a signal of unknown frequency characteristics utilizing a code generator responsive to a timing signal to generate a series of repetitive frames of sampling pulses, where each frame represents a series of cross-correlation functions in terms of a predetermined number of sampling intervals and a predetermined number of harmonics defined by a two-dimensional sample weighting matrix formed by approximating a series of harmonically related cross-correlation functions in which each column of the matrix corresponds to a different sampling interval, while each row corresponds to a different harmonic of the cross-correlation function. These sampling pulses are then multiplied with the incoming signal to generate a train of discrete sampled outputs which are accumulated.
During each successive sampling interval, the code generator scans a successive column of the sampled weighting matrix to generate a series of harmonically related cross-correlation functions. The scanning sequence is repeated with each sampling pulse produced by the code generator being a function of the sampling interval and the harmonic of the cross-correlation function. After the scan of the last column of each scanning sequence, the accumulated output represents the desired frequency spectrum of the unknown signal based upon the multiplication of an unknown time domain signal with a series of signals of known frequency, where each product is integrated over a finite time period.
U.S. Pat. No. 4,093,989 discloses in FIG. 3 the basic concept of a proportional bandwidth spectrum analyzer comprised of a bandpass (BP) filter for sampling the signal at a known frequency and then processing the digital samples using a Fast Fourier Transform algorithm, and in FIG. 4 the implementation of a proportional bandwidth analysis that overcomes limitations of multiplier speed and memory capacity. A controller in the digital processor selects the bandwidth of the lowpass filter and selects the sampling frequency, both of which must be known in order for the processor to carry out spectrum analysis. The analysis range is separated into a number of ranges, e.g., 0-20 kHz, 0-2000 Hz and 0-200 Hz, and a block of samples is collected for each range. Each block is multiplied by a weighting function before processing in a serial-parallel fashion by digital filtering, squaring and integrating. The effect of the weighting function is to contain the spectral energy of a short data block of a sinewave within the bandpass filter.
These references underscore the limitations of the prior art in the multiplier and memory capacity required for spectrum analysis using known techniques. An object of the present invention is to provide a method and apparatus for real-time frequency spectrum analysis free of these limitations.